If you could have one superpower to help you in your work, what would it be?
” I would say it would be to have an intelligent search engine, which can help me solve all the technical problems that the different internal stakeholders encounter daily. Something that could even help me with my tasks. You know, something that really looks like ChatGPT. If it gives me the solution and performs the action, I think that would be what everyone would want in tasks like ours. With that, I could expose the problem and so it would be both detected and fixed. ”
Is it necessary to have a data analyst to maintain a company?
I would say yes. You know, a report or a dashboard from a data analyst, it helps the board of directors, the senior management, to make strategic decisions based on the data that the data analyst has provided. So, to make strategic decisions, to attract funding, you must make a nice picture of that data, because it can end up in big offices. The value that this data can bring to the company makes it very important to have a data analyst presence.
There are more than just those in my role. There is also, in other organization charts, a data scientist who is used to do other things upstream, preventively, for the future. My role as a data analyst is more focused on immediate needs. It allows us to justify and help with the decision. He does decision analysis. The data analyst must tell a story from the data, and that’s what helps to know the options, because the data speaks for itself. It helps to show anomalies, holes…
We’re not into big data, because we don’t really have large amounts of data like millions of lines coming in for streaming. We have smaller amounts of data, so one data analyst is enough to do all that. But it’s true that other organizations that are bigger than us in terms of volume, velocity, variety and veracity of data, they have complete teams of data modeler, data analyst, ETL developer, data steward, data scientist, data engineer…. etc.
You see, there are several data roles. Organizations that receive new data every second, or in batch, need a team ready to receive it.
If we take a solution, it starts from the data collection, the extraction of the data; that comes in the backend. This is the moment when you model, conceptualize, to know where your data will go. Then you do the extraction, the transformation, the loading. And from there, we move to the frontend, which is the visualization. This is where we translate everything we’ve done into dashboards and reports, so that senior management can make informed decisions. They want to see KPIs, performance indicators, and I ensure the fluidity of all this, from the backend to the frontend. ”
Communications – Centech
Mélina Cyr St-André